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Research on Failure Precursor of Water-Soaked Coal-Rock Based on Acoustic Emission Dominant Signals Screening
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Haiyan Su1, 2, 3, Jun Zhu1, 2, Ziming Liu1, 2, Yuanjun Ma4, Yong Zhang5
Mining Research and Development | 2026, 46(6) : 129 - 139
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Mining Research and Development | 2026, 46(6): 129-139
Research on Failure Precursor of Water-Soaked Coal-Rock Based on Acoustic Emission Dominant Signals Screening
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Haiyan Su1, 2, 3, Jun Zhu1, 2, Ziming Liu1, 2, Yuanjun Ma4, Yong Zhang5
Affiliations
  • 1.Institution of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan 610299, China
  • 2.Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese Academy of Sciences, Chengdu, Sichuan 610299, China
  • 3.University of Chinese Academy of Sciences, Beijing 101408, China
  • 4.School of Logistics, Chengdu University of Information Technology, Chengdu, Sichuan 610225, China
  • 5.State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 102209, China
Published: 2026-06-18
Outline
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To address the problem that low-energy acoustic emission (AE) signals account for an excessively high proportion during the fracture process of water-soaked coal-rock, high-energy critical information to be easily masked, resulting in insufficient accuracy in failure precursor identification, synchronous uniaxial compression and acoustic emission tests were conducted on coal-rock specimens under natural conditions and after 120 h of water-soaked. Based on the energy contribution rate and damage stress, a novel AE signal screening method was developed to extract dominant signals during coal-rock failure and investigate their precursory characteristics. The results show that water-soaked significantly decreases the uniaxial compressive strength of coal-rock. Compared with specimens under natural conditions, the average uniaxial compressive strength of water-soaked coal-rock decreases by 14.79%. Cracks exhibite multidirectional propagation behavior, thereby aggravating the final failure of the coal-rock. The cumulative AE count of coal-rock specimens under natural conditions reach 4×106, while that of water-soaked specimens decrease to 2×106. Moreover, the evolution of the cumulative AE count shows good agreement with the stress-strain behavior of the coal-rock. The AE dominant signal extraction method based on the energy contribution rate and damage-stress time window effectively identifies dominant signals during the failure process of water-soaked coal-rock. Compared with coal-rock under natural conditions, the extracted dominant signals exhibite lower energy thresholds but higher signal proportions. Furthermore, the extracted dominant signals show strong correspondence with the failure precursors of water-soaked coal-rock. These findings provide a theoretical basis for engineering stability prediction.

Water-soaked coal-rock  /  Dominant signals screening  /  Precursory characteristy  /  Uniaxial compressive strength  /  Acoustic emission ringing count
苏海燕, 朱俊, 刘子明, 马元军, 张勇. 基于声发射优势信号筛选的浸水煤岩破坏前兆研究. 矿业研究与开发, 2026 , 46 (6) : 129 -139 .
Haiyan Su, Jun Zhu, Ziming Liu, Yuanjun Ma, Yong Zhang. Research on Failure Precursor of Water-Soaked Coal-Rock Based on Acoustic Emission Dominant Signals Screening[J]. Mining Research and Development, 2026 , 46 (6) : 129 -139 .
Year 2026 volume 46 Issue 6
32
7
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Article Info
  • Receive Date:2025-05-28
  • Online Date:2026-10-27
  • Published:2026-06-18
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  • Received:2025-05-28
Funding
Affiliations
    1.Institution of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, Sichuan 610299, China
    2.Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese Academy of Sciences, Chengdu, Sichuan 610299, China
    3.University of Chinese Academy of Sciences, Beijing 101408, China
    4.School of Logistics, Chengdu University of Information Technology, Chengdu, Sichuan 610225, China
    5.State Key Laboratory of Water Resource Protection and Utilization in Coal Mining, Beijing 102209, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)
属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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